Digital society social interactions and trust analysis model

• Published in: PeerJ. Computer science Vol. 8; p. e1129
• Main Authors: Kumar, Aseem, Malik, Arun, Batra, Isha, Ahmad, Naveed, Johar, Sumaira
• Format: Journal Article
• Language: English
• Published: United States PeerJ. Ltd 13-12-2022; PeerJ, Inc; PeerJ Inc
• Subjects: Analysis; COVID-19; Digital sociology; Disinformation; Epidemics; mediocristan; Pandemics; Scientific Computing and Simulation; Sentiment analysis; Social aspects; Social Computing; Social factors; Society; Trust model; COVID-19; Sentiment analysis; Extremistan; Digital sociology; mediocristan; Society; Trust model
• ISSN: 2376-5992; 2376-5992
• DOI: 10.7717/PEERJ-CS.1129

During unprecedented events such as COVID-19, the fabric of society comes under stress and all stakeholders want to increase the predictability of the future and reduce the ongoing uncertainties. In this research, an attempt has been made to model the situation in which the sentiment "trust" is computed so as to map the behaviour of society. However, technically, the purpose of this research is not to determine the "degree of trust in society" as a consequence of some specific emotions or sentiments that the community is experiencing at any particular time. This project is concerned with the construction of a computational model that can assist in improving our understanding of the dynamics of digital societies, particularly when it comes to the attitude referred to as "trust." The digital society trust analysis (D.S.T.A.) model that has been provided is simple to configure and simple to implement. It includes many previous models, such as standing models, Schelling's model of segregation, and tipping points, in order to construct models for understanding the dynamics of a society reeling under the effects of a COVID-19 pandemic, misinformation, fake news, and other sentiments that impact the behaviour of the different groups.